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Organisationseinheit der BAM
A modern day light microscope has evolved from a tool devoted to making primarily empirical observations to what is now a sophisticated, quantitative device that is an integral part of both physical and life science research. Nowadays, microscopes are found in nearly every experimental laboratory. However, despite their prevalent use in capturing and quantifying scientific phenomena, neither a thorough understanding of the principles underlying quantitative imaging techniques nor appropriate knowledge of how to calibrate, operate and maintain microscopes can be taken for granted. This is clearly demonstrated by the well-documented and widespread difficulties that are routinely encountered in evaluating acquired data and reproducing scientific experiments. Indeed, studies have shown that more than 70% of researchers have tried and failed to repeat another scientist’s experiments, while more than half have even failed to reproduce their own experiments1. One factor behind the reproducibility crisis of experiments published in scientific journals is the frequent underreporting of imaging methods caused by a lack of awareness and/or a lack of knowledge of the applied technique2,3. Whereas quality control procedures for some methods used in biomedical research, such as genomics (e.g., DNA sequencing, RNA-seq) or cytometry, have been introduced (e.g. ENCODE4), this issue has not been tackled for optical microscopy instrumentation and images. Although many calibration standards and protocols have been published, there is a lack of awareness and agreement on common Standards and guidelines for quality assessment and reproducibility5.
In April 2020, the QUality Assessment and REProducibility for instruments and images in Light Microscopy (QUAREP-LiMi) initiative6 was formed. This initiative comprises imaging scientists from academia and industry who share a common interest in achieving a better understanding of the performance and limitations of microscopes and improved quality control (QC) in light microscopy. The ultimate goal of the QUAREP-LiMi initiative is to establish a set of common QC standards, guidelines, metadata models7,8, and tools9,10, including detailed protocols, with the ultimate aim of improving reproducible advances in scientific research.
This White Paper 1) summarizes the major obstacles identified in the field that motivated the launch of the QUAREP-LiMi initiative; 2) identifies the urgent need to address these obstacles in a grassroots manner, through a community of Stakeholders including, researchers, imaging scientists11, bioimage analysts, bioimage informatics developers, corporate partners, Funding agencies, standards organizations, scientific publishers, and observers of such; 3) outlines the current actions of the QUAREPLiMi initiative, and 4) proposes future steps that can be taken to improve the dissemination and acceptance of the proposed guidelines to manage QC.
To summarize, the principal goal of the QUAREP-LiMi initiative is to improve the overall quality and reproducibility of light microscope image data by introducing broadly accepted standard practices and accurately captured image data metrics.
Unity in defence: honeybee workers exhibit conserved molecular responses to diverse pathogens
(2017)
Background: Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses.
Results: We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses.
Conclusions: Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions.
Stress is a normal part of life for fungi, which can survive in environments considered inhospitable or hostile for other organisms. Due to the ability of fungi to respond to, survive in, and transform the environment, even under severe stresses, many researchers are exploring the mechanisms that enable fungi to adapt to stress. The International Symposium on Fungal Stress (ISFUS) brings together leading scientists from around the world who research fungal stress. This article discusses presentations given at the third ISFUS, held in Sao Jose dos Campos, Sao Paulo, Brazil in 2019, thereby summarizing the state-of-the-art knowledge on fungal stress, a field that includes microbiology, agriculture, ecology, biotechnology, medicine, and astrobiology.
Emerging infectious diseases (EIDs) have contributed significantly to the current biodiversity crisis, leading to widespread epidemics and population loss. Owing to genetic variation in pathogen virulence, a complete understanding of species decline requires the accurate identification and characterization of EIDs. We explore this issue in the Western honeybee, where increasing mortality of populations in the Northern Hemisphere has caused major concern. Specifically, we investigate the importance of genetic identity of the main suspect in mortality, deformed wing virus (DWV), in driving honeybee loss. Using laboratory experiments and a systematic field survey, we demonstrate that an emerging DWV genotype (DWV-B) is more virulent than the established DWV genotype (DWV-A) and is widespread in the landscape. Furthermore, we show in a simple model that colonies infected with DWV-B collapse sooner than colonies infected with DWV-A. We also identify potential for rapid DWV evolution by revealing extensive genome-wide recombination in vivo. The emergence of DWV-B in naive honeybee populations, including via recombination with DWV-A, could be of significant ecological and economic importance. Our findings emphasize that knowledge of pathogen genetic identity and diversity is critical to understanding drivers of species decline.
Comparison of traceable methods for determining the calorific value of non-conventional fuel gases
(2016)
Energy-content measurements by direct methods (such as calorimetry) are used to validate the indirect method (from gas composition obtained by gas chromatography) which is generally adopted by grid operators for on-site gas control. A primary reference gas calorimeter and three field calorimeters were used for the first time to measure accurately the energy content of non-conventional gases (biogas and coal mine methane). The gas mixtures for this study were prepared by gravimetry and comprised three binary mixtures containing carbon dioxide and (up to 80 mol-%) methane, three ternary mixtures containing carbon dioxide, (up to 70 mol-%) methane and (up to 0.3 mol-%) hydrogen sulphide as well as a ten-component mixture with a methane content of approximately 64 mol-% which represents a typical coal mine methane. Associated uncertainty calculations were developed for each instrument and are presented here. Traceability of the measurements to the SI units is ensured in reference calorimetry, as calibration is accomplished by electrical simulation based on the Joule effect in order to obtain the heat capacity of the entire system. The results obtained with the four calorimeters are compared with each other and also with results calculated from the indirect method that is based on gas chromatography. Uncertainties (k = 2) between 0.07 and 0.49% for the reference gases were obtained with the reference calorimeter, while uncertainties for the field calorimeters range between 0.18 and 2.48% for the same mixtures. Compared to the usual standard deviation observed by gas chromatography for a multicomponent gas mixture of about 1%, it is demonstrated that the calorimetric method, although rarely used for non-conventional gases before, is appropriate for energy-content measurements of gases originating from renewable energy sources.
A sting in the spit: widespread cross-infection of multiple RNA viruses across wild and managed bees
(2015)
1.Declining populations of bee pollinators are a cause of concern, with major repercussions for biodiversity loss and food security. RNA viruses associated with honeybees represent a potential threat to other insect pollinators, but the extent of this threat is poorly understood.
2.This study aims to attain a detailed understanding of the current and ongoing risk of emerging infectious disease (EID) transmission between managed and wild pollinator species across a wide range of RNA viruses.
3.Within a structured large-scale national survey across 26 independent sites, we quantify the prevalence and pathogen loads of multiple RNA viruses in co-occurring managed honeybee (Apis mellifera) and wild bumblebee (Bombus spp.) populations. We then construct models that compare virus prevalence between wild and managed pollinators.
4.Multiple RNA viruses associated with honeybees are widespread in sympatric wild bumblebee populations. Virus prevalence in honeybees is a significant predictor of virus prevalence in bumblebees, but we remain cautious in speculating over the principle direction of pathogen transmission. We demonstrate species-specific differences in prevalence, indicating significant variation in disease susceptibility or tolerance. Pathogen loads within individual bumblebees may be high and in the case of at least one RNA virus, prevalence is higher in wild bumblebees than in managed honeybee populations.
5.Our findings indicate widespread transmission of RNA viruses between managed and wild bee pollinators, pointing to an interconnected network of potential disease pressures within and among pollinator species. In the context of the biodiversity crisis, our study emphasizes the importance of targeting a wide range of pathogens and defining host associations when considering potential drivers of population decline.
Emerging infectious diseases (EIDs) pose a risk to human welfare, both directly1 and indirectly, by affecting managed livestock and wildlife that provide valuable resources and ecosystem services, such as the pollination of crops2. Honeybees (Apis mellifera), the prevailing managed insect crop pollinator, suffer from a range of emerging and exotic high-impact pathogens3,4, and population maintenance requires active management by beekeepers to control them. Wild pollinators such as bumblebees (Bombus spp.) are in global decline5,6, one cause of which may be pathogen spillover from managed pollinators like honeybees7,8 or commercial colonies of bumblebees9. Here we use a combination of infection experiments and landscape-scale field data to show that honeybee EIDs are indeed widespread infectious agents within the pollinator assemblage. The prevalence of deformed wing virus (DWV) and the exotic parasite Nosema ceranae in honeybees and bumblebees is linked; as honeybees have higher DWV prevalence, and sympatric bumblebees and honeybees are infected by the same DWV strains, Apis is the likely source of at least one major EID in wild pollinators. Lessons learned from vertebrates10,11 highlight the need for increased pathogen control in managed bee species to maintain wild pollinators, as declines in native pollinators may be caused by interspecies pathogen transmission originating from managed pollinators.
Emerging infectious diseases arise as a result of novel interactions between populations of hosts and pathogens, and can threaten the health and wellbeing of the entire spectrum of biodiversity. Bees andtheir viruses area case in point. However, detailed knowledge of the ecological factors and evolutionary forces that drive disease emergence in bees and other host–pathogen communities is surprisingly lacking. In this review, we build on the fundamental insight that viruses evolve and adapt over timescales that overlap with host ecology. At the same time, we integrate the role of host community ecology, including community structure and composition, biodiversity loss, and human driven disturbance, all of which represent significant factors in bee virus ecology. Both of these evolutionary and ecological perspectives represent major advances but, in most cases, it remains unclear how evolutionary forces actually operate across different biological scales (e.g., from cell to ecosystem). We present a molecule-to-ecology framework to help address these issues, emphasizing the role of molecular mechanisms as keybottom-up drivers of change at higher ecological scales. We consider the bee–virus system to be an ideal one in which to apply this framework. Unlike many other animal models, bees constitute a well characterized and accessible multispecies assemblage, whose populations and interspecific interactions can be experimentally manipulated and monitored in high resolution across space and time to provide robust tests of prevailing theory.